Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A method comprising: obtaining, responsive to a search query submitted by a user, a result set, the result set comprising a set of pages; determining a first personality score of a first page in the set of pages using a value of a personality trait of the user, a weight associated with the value, and a personality score of an author of the first page, the personality score of the author being based on a personality analysis of another content published by the author, wherein the personality score of the first page is based on a plurality of personality traits computed for the first page, the plurality of personality traits comprising a first trait to indicate an extraversion trait, a trust trait, a harmony trait, and a melancholy trait according to a Big 5 personality traits model; determining a second personality score of a second page in the set of pages using the value of the personality trait of the user, the weight associated with the value, and a second personality score of a second author of the second page, the second personality score of the second author being based on a second personality analysis of a different content published by the second author; ordering, responsive to the first personality score exceeding the second personality score, the first page ahead of the second page in the result set to form a rearranged result set; presenting the rearranged result set such that the user finds the first page which is more compatible with the user's personality traits listed before the second pages less compatible with the user's personality traits, even when the first page and the second page are equally relevant to the search query; analyzing, using English Slot Grammar technique, the first page to determine a grammatical expression in the page, wherein the grammatical expression comprises a sentence structure in the page; identifying, from a personality model, a personality trait of the first page corresponding to the grammatical expression, the identified personality trait comprising a conscientious trait; computing a value of the personality trait of the first page according to a value of the grammatical expression; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
A method for personalizing search results involves obtaining a set of pages in response to a user's search query. It determines a personality score for each page based on the user's personality traits, a weight associated with those traits, and the author's personality, analyzing content they've published. The page's personality is assessed using traits like extraversion, trust, harmony, and melancholy from the Big 5 model. Pages are then reordered, placing those with higher personality scores (better match to the user's profile) ahead of others, even if their relevance to the search query is the same. The page's grammatical structure, analyzed using English Slot Grammar, is used to derive a conscientious trait, and a corresponding value is assigned.
2. The method of claim 1 , further comprising: receiving a selection input relative to the rearranged result set, the selection indicating a user preference of ordering a third page according to the user's personality traits; and adjusting a value corresponding to a trait in the user's personality traits to change the order of the third page according to the user's preference.
The method for personalizing search results, as described above, also involves receiving user input regarding the ordering of search results. If a user indicates a preference for a different ordering of a particular page based on personality, the system adjusts the weighting or values associated with specific personality traits in the user's profile to better reflect the user's preference, thereby changing the order of the results to better suit the user's personality. Specifically, the system adjusts a value corresponding to a trait in the user's personality traits to change the order of the third page according to the user's preference.
3. The method of claim 1 , further comprising: constructing a personality profile of the user by determining a set of personality traits of the user according to a personality model, the set of personality traits including the personality trait; computing a value for each personality trait in the set of personality traits; and adding each personality trait from the set of personality traits and a corresponding value as a distinct personality data in the personality profile.
The method for personalizing search results, as described above, further involves constructing a detailed personality profile for each user. This profile is created by identifying a range of personality traits according to a defined personality model, calculating a specific value for each identified trait. Each personality trait and its corresponding value are then stored as distinct data points within the user's personality profile. This profile data is then used to improve the accuracy of search result ordering by improving matching the user's personality. Specifically, it includes constructing a personality profile of the user by determining a set of personality traits of the user according to a personality model, the set of personality traits including the personality trait; computing a value for each personality trait in the set of personality traits; and adding each personality trait from the set of personality traits and a corresponding value as a distinct personality data in the personality profile.
4. The method of claim 1 , further comprising: computing a page-specific personality score of the first page; computing an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, and (ii) the page-specific personality score of the first page; and using the overall personality score in the first personality score of the first page.
The method for personalizing search results, as described above, also computes a page-specific personality score for each page and then computes an overall personality score for each page. This overall score considers both the page-specific score and a personality score derived from the website hosting the page, based on analyzing other content on that site. This overall personality score is then used when determining the page's final personality score, influencing its ranking in the search results. Specifically, the method further includes computing a page-specific personality score of the first page; computing an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, and (ii) the page-specific personality score of the first page; and using the overall personality score in the first personality score of the first page.
5. The method of claim 1 , further comprising: computing a page-specific personality score of the first page; computing an overall personality score of the first page using the personality score of the author and the page-specific personality score of the first page; and using the overall personality score in the first personality score of the first page.
The method for personalizing search results, as described above, also calculates a page-specific personality score and combines it with the author's personality score to create an overall personality score for the page. This overall score, combining the page's content and the author's traits, is then used to determine the page's position in the search results, ensuring that pages from authors with compatible personalities are prioritized. Specifically, the method further includes computing a page-specific personality score of the first page; computing an overall personality score of the first page using the personality score of the author and the page-specific personality score of the first page; and using the overall personality score in the first personality score of the first page.
6. The method of claim 1 , further comprising: computing a page-specific personality score of the first page; computing an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, (ii) the personality score of the author, and (iii) the page-specific personality score of the first page; and using the overall personality score in the first personality score of the first page.
The method for personalizing search results, as described above, also involves combining several personality scores to determine a final ranking. It calculates a page-specific score, factors in the personality of the author, and also considers the overall personality of the website hosting the content. All these scores are combined to create an overall personality score for the page, which then dictates its placement in the personalized search results. Specifically, the method further includes computing a page-specific personality score of the first page; computing an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, (ii) the personality score of the author, and (iii) the page-specific personality score of the first page; and using the overall personality score in the first personality score of the first page.
7. The method of claim 1 , further comprising: analyzing the first page to determine a sentiment in the page; identifying, from a personality model, a personality trait of the first page corresponding to the sentiment; computing a value of the personality trait of the first page according to a value of the sentiment; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
The method for personalizing search results, as described above, also analyzes each page to determine its sentiment (positive, negative, neutral). Based on this sentiment analysis, it identifies a corresponding personality trait and assigns a value to that trait. This personality trait and its value are then added to the page's personality data, influencing its ranking in the search results based on its emotional tone and how well it aligns with the user's personality. Specifically, it includes analyzing the first page to determine a sentiment in the page; identifying, from a personality model, a personality trait of the first page corresponding to the sentiment; computing a value of the personality trait of the first page according to a value of the sentiment; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
8. The method of claim 1 , further comprising: analyzing the first page to determine a semantic expression in the page; identifying, from a personality model, a personality trait of the first page corresponding to the semantic expression; computing a value of the personality trait of the first page according to a value of the semantic expression; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
The method for personalizing search results, as described above, analyzes each page to identify its semantic expressions and relates these to personality traits. A value is computed for the identified trait based on the expression, and this trait and its value are added to the page's personality profile. This data then influences how the page is ranked in search results, based on semantic content compatibility with a user's personality. Specifically, it includes analyzing the first page to determine a semantic expression in the page; identifying, from a personality model, a personality trait of the first page corresponding to the semantic expression; computing a value of the personality trait of the first page according to a value of the semantic expression; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
9. The method of claim 1 , further comprising: analyzing the first page to determine a diversity of references in the page; identifying, from a personality model, a personality trait of the first page corresponding to the diversity of the references; computing a value of the personality trait of the first page according to a value of the diversity of the references; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
The method for personalizing search results, as described above, also involves analyzing the diversity of references cited within a page. A corresponding personality trait is identified, and its value is computed based on the reference diversity. This trait and value are added to the page's data, affecting its search result ranking based on how its citation diversity aligns with the user's personality. Specifically, it includes analyzing the first page to determine a diversity of references in the page; identifying, from a personality model, a personality trait of the first page corresponding to the diversity of the references; computing a value of the personality trait of the first page according to a value of the diversity of the references; and assigning to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
10. The method of claim 1 , further comprising: obtaining, responsive to a partial input of the search query, a set of type-ahead options to complete the search query input; and ordering a first type-ahead option before a second type-ahead option in the set of type-ahead options responsive to the first type-ahead option relating to a personality trait of the user to a greater degree than the second type-ahead option.
In the method for personalizing search results, as described above, when a user begins typing a search query, a set of type-ahead (autocomplete) options are presented. These options are ordered based on how strongly they relate to the user's personality traits, such that options more aligned with the user's personality appear higher in the list, enabling a more personalized and efficient search experience from the very beginning. Specifically, the system involves obtaining, responsive to a partial input of the search query, a set of type-ahead options to complete the search query input; and ordering a first type-ahead option before a second type-ahead option in the set of type-ahead options responsive to the first type-ahead option relating to a personality trait of the user to a greater degree than the second type-ahead option.
11. The method of claim 1 , wherein the method is embodied in a computer program product comprising one or more computer-readable storage devices and computer-readable program instructions which are stored on the one or more computer-readable storage devices and executed by one or more processors.
The method described in Claim 1, which involves personalizing search results based on user and content personality analysis, is implemented as a computer program product stored on computer-readable storage devices and executed by one or more processors.
12. The method of claim 1 , wherein the method is embodied in a computer system comprising one or more processors, one or more computer-readable memories, one or more computer-readable storage devices and program instructions which are stored on the one or more computer-readable storage devices for execution by the one or more processors via the one or more memories and executed by the one or more processors.
The method described in Claim 1, which involves personalizing search results based on user and content personality analysis, is implemented within a computer system including processors, memory, and storage devices, with program instructions stored for execution by the processors.
13. A computer program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising: program instructions to obtain, responsive to a search query submitted by a user, a result set, the result set comprising a set of pages; program instructions to determine a first personality score of a first page in the set of pages using a value of a personality trait of the user, a weight associated with the value, and a personality score of an author of the first page, the personality score of the author being based on a personality analysis of another content published by the author, wherein the personality score of the first page is based on a plurality of personality traits computed for the first page, the plurality of personality traits comprising a first trait to indicate an extraversion trait, a trust trait, a harmony trait, and a melancholy trait according to a Big 5 personality traits model; program instructions to determine a second personality score of a second page in the set of pages using the value of the personality trait of the user, the weight associated with the value, and a second personality score of a second author of the second page, the second personality score of the second author being based on a second personality analysis of a different content published by the second author; program instructions to order, responsive to the first personality score exceeding the second personality score, the first page ahead of the second page in the result set to form a rearranged result set; program instructions to present the rearranged result set such that the user finds the first page which is more compatible with the user's personality traits listed before the second pages less compatible with the user's personality traits, even when the first page and the second page are equally relevant to the search query; program instructions to analyze, using English Slot Grammar technique, the first page to determine a grammatical expression in the page, wherein the grammatical expression comprises a sentence structure in the page; program instructions to identify, from a personality model, a personality trait of the first page corresponding to the grammatical expression, the identified personality trait comprising a conscientious trait; program instructions to compute a value of the personality trait of the first page according to a value of the grammatical expression; and program instructions to assign to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
A computer program product personalizes search results by obtaining a set of pages in response to a user's query. It determines a personality score for each page using the user's traits, weighted values, and author personality derived from their content. Page personalities are assessed using traits from the Big 5 model (extraversion, trust, harmony, melancholy). Pages are reordered to prioritize matches to the user's personality, even if query relevance is equal. Grammatical analysis (English Slot Grammar) derives a conscientiousness trait and value for the page. The program analyzes grammatical expressions in the page to determine the page's conscientious trait, then computes a value, and then assigns a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
14. The computer program product of claim 13 , further comprising: program instructions to receive a selection input relative to the rearranged result set, the selection indicating a user preference of ordering a third page according to the user's personality traits; and program instructions to adjust a value corresponding to a trait in the user's personality traits to change the order of the third page according to the user's preference.
The computer program product for personalizing search results, as described above, allows users to provide feedback on the ordering of results. If a user reorders a page based on personality, the program adjusts the weighting of user personality traits to reflect this preference, changing the results order accordingly. Specifically, it further includes program instructions to receive a selection input relative to the rearranged result set, the selection indicating a user preference of ordering a third page according to the user's personality traits; and program instructions to adjust a value corresponding to a trait in the user's personality traits to change the order of the third page according to the user's preference.
15. The computer program product of claim 13 , further comprising: program instructions to construct a personality profile of the user by determining a set of personality traits of the user according to a personality model, the set of personality traits including the personality trait; program instructions to compute a value for each personality trait in the set of personality traits; and program instructions to add each personality trait from the set of personality traits and a corresponding value as a distinct personality data in the personality profile.
The computer program product for personalizing search results, as described above, constructs user personality profiles. These profiles identify personality traits based on a model, compute values for each, and store them as data within the user's profile to improve search result personalization. Specifically, the computer program product further includes program instructions to construct a personality profile of the user by determining a set of personality traits of the user according to a personality model, the set of personality traits including the personality trait; program instructions to compute a value for each personality trait in the set of personality traits; and program instructions to add each personality trait from the set of personality traits and a corresponding value as a distinct personality data in the personality profile.
16. The computer program product of claim 13 , further comprising: program instructions to compute a page-specific personality score of the first page; program instructions to compute an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, and (ii) the page-specific personality score of the first page; and program instructions to use the overall personality score in the first personality score of the first page.
The computer program product for personalizing search results, as described above, calculates a page-specific personality score and an overall score that considers the website's personality (derived from its content). The overall score, combining page and website traits, is used to rank the search results. Specifically, it includes program instructions to compute a page-specific personality score of the first page; program instructions to compute an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, and (ii) the page-specific personality score of the first page; and program instructions to use the overall personality score in the first personality score of the first page.
17. The computer program product of claim 13 , further comprising: program instructions to compute a page-specific personality score of the first page; program instructions to compute an overall personality score of the first page using the personality score of the author and the page-specific personality score of the first page; and program instructions to use the overall personality score in the first personality score of the first page.
The computer program product for personalizing search results, as described above, calculates a page-specific personality score and combines it with the author's personality score to create an overall score. This overall score, combining page and author traits, is used to rank the search results. Specifically, it includes program instructions to compute a page-specific personality score of the first page; program instructions to compute an overall personality score of the first page using the personality score of the author and the page-specific personality score of the first page; and program instructions to use the overall personality score in the first personality score of the first page.
18. The computer program product of claim 13 , further comprising: program instructions to compute a page-specific personality score of the first page; program instructions to compute an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, (ii) the personality score of the author, and (iii) the page-specific personality score of the first page; and program instructions to use the overall personality score in the first personality score of the first page.
The computer program product for personalizing search results, as described above, calculates a page-specific personality score and combines it with both the author's personality score and the website's personality score. This comprehensive overall score is then used to rank the search results. Specifically, it includes program instructions to compute a page-specific personality score of the first page; program instructions to compute an overall personality score of the first page using (i) a personality score of the site from which the first page is obtained, the personality score of the site being based on a personality analysis of another content on the site, (ii) the personality score of the author, and (iii) the page-specific personality score of the first page; and program instructions to use the overall personality score in the first personality score of the first page.
19. A computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising: program instructions to obtain, responsive to a search query submitted by a user, a result set, the result set comprising a set of pages; program instructions to determine a first personality score of a first page in the set of pages using a value of a personality trait of the user, a weight associated with the value, and a personality score of an author of the first page, the personality score of the author being based on a personality analysis of another content published by the author, wherein the personality score of the first page is based on a plurality of personality traits computed for the first page, the plurality of personality traits comprising a first trait to indicate an extraversion trait, a trust trait, a harmony trait, and a melancholy trait according to a Big 5 personality traits model; program instructions to determine a second personality score of a second page in the set of pages using the value of the personality trait of the user, the weight associated with the value, and a second personality score of a second author of the second page, the second personality score of the second author being based on a second personality analysis of a different content published by the second author; program instructions to order, responsive to the first personality score exceeding the second personality score, the first page ahead of the second page in the result set to form a rearranged result set; program instructions to present the rearranged result set such that the user finds the first page which is more compatible with the user's personality traits listed before the second pages less compatible with the user's personality traits, even when the first page and the second page are equally relevant to the search query; program instructions to analyze, using English Slot Grammar technique, the first page to determine a grammatical expression in the page, wherein the grammatical expression comprises a sentence structure in the page; program instructions to identify, from a personality model, a personality trait of the first page corresponding to the grammatical expression, the identified personality trait comprising a conscientious trait; program instructions to compute a value of the personality trait of the first page according to a value of the grammatical expression; and program instructions to assign to the first page a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
A computer system personalizes search results by obtaining a set of pages in response to a user's query. It determines a personality score for each page using the user's traits, weighted values, and author personality derived from their content. Page personalities are assessed using traits from the Big 5 model (extraversion, trust, harmony, melancholy). Pages are reordered to prioritize matches to the user's personality, even if query relevance is equal. Grammatical analysis (English Slot Grammar) derives a conscientiousness trait and value for the page. The program analyzes grammatical expressions in the page to determine the page's conscientious trait, then computes a value, and then assigns a personality data comprising the personality trait of the first page and the value of the personality trait of the first page.
Unknown
August 29, 2017
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